Daniel Nyga

428 total citations
13 papers, 247 citations indexed

About

Daniel Nyga is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Aerospace Engineering. According to data from OpenAlex, Daniel Nyga has authored 13 papers receiving a total of 247 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 2 papers in Aerospace Engineering. Recurrent topics in Daniel Nyga's work include Natural Language Processing Techniques (8 papers), AI-based Problem Solving and Planning (7 papers) and Topic Modeling (5 papers). Daniel Nyga is often cited by papers focused on Natural Language Processing Techniques (8 papers), AI-based Problem Solving and Planning (7 papers) and Topic Modeling (5 papers). Daniel Nyga collaborates with scholars based in Germany. Daniel Nyga's co-authors include Michael Beetz, Moritz Tenorth, Ferenc Bálint-Benczédi, Nico Blodow, Zoltán-Csaba Márton, Mihai Pomarlan, Nicholas Roy, Rohan Paul, Subhro Roy and Daehyung Park and has published in prestigious journals such as elib (German Aerospace Center), Adaptive Agents and Multi-Agents Systems and Media (https://www.suub.uni-bremen.de/).

In The Last Decade

Daniel Nyga

13 papers receiving 233 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Daniel Nyga Germany	7	161	107	106	21	16	13	247
Jacob Arkin United States	8	156 1.0×	109 1.0×	66 0.6×	15 0.7×	13 0.8×	17	262
Mihai Pomarlan Germany	7	117 0.7×	72 0.7×	94 0.9×	22 1.0×	14 0.9×	25	219
Tim Niemueller Germany	7	88 0.5×	63 0.6×	79 0.7×	21 1.0×	24 1.5×	12	187
Daniel Beßler Germany	6	135 0.8×	59 0.6×	108 1.0×	13 0.6×	11 0.7×	9	235
Asil Kaan Bozcuoğlu Germany	8	140 0.9×	65 0.6×	123 1.2×	14 0.7×	18 1.1×	15	240
Dipendra Misra United States	7	250 1.6×	174 1.6×	86 0.8×	11 0.5×	20 1.3×	11	320
Glen Chou United States	9	89 0.6×	85 0.8×	54 0.5×	7 0.3×	6 0.4×	17	188
Anchit Gupta India	8	278 1.7×	115 1.1×	52 0.5×	7 0.3×	3 0.2×	14	346
Bradly C. Stadie United States	5	124 0.8×	57 0.5×	65 0.6×	7 0.3×	4 0.3×	9	177
Luc Julia United States	7	92 0.6×	67 0.6×	18 0.2×	20 1.0×	14 0.9×	15	168

Countries citing papers authored by Daniel Nyga

Since Specialization

Citations

This map shows the geographic impact of Daniel Nyga's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Nyga with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Nyga more than expected).

Fields of papers citing papers by Daniel Nyga

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Nyga. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Nyga. The network helps show where Daniel Nyga may publish in the future.

Co-authorship network of co-authors of Daniel Nyga

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Nyga. A scholar is included among the top collaborators of Daniel Nyga based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel Nyga. Daniel Nyga is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

1.

Nyga, Daniel, Subhro Roy, Rohan Paul, et al.. (2018). Grounding Robot Plans from Natural Language Instructions with Incomplete World Knowledge. 714–723. 15 indexed citations

2.

Pomarlan, Mihai, et al.. (2017). Deeper Understanding of Vague Instructions through Simulated Execution. Adaptive Agents and Multi-Agents Systems. 1694–1696. 1 indexed citations

3.

Pomarlan, Mihai, et al.. (2017). Deeper Understanding of Vague Instructions through Simulated Execution (Extended Abstract). Adaptive Agents and Multi-Agents Systems. 2 indexed citations

4.

Nyga, Daniel, et al.. (2017). What no robot has seen before — Probabilistic interpretation of natural-language object descriptions. 4278–4285. 6 indexed citations

5.

Nyga, Daniel, et al.. (2017). Instruction completion through instance-based learning and semantic analogical reasoning. 4270–4277. 5 indexed citations

6.

Nyga, Daniel. (2017). Interpretation of Natural-language Robot Instructions: Probabilistic Knowledge Representation, Learning, and Reasoning. Media (https://www.suub.uni-bremen.de/). 1 indexed citations

7.

Beetz, Michael, et al.. (2015). RoboSherlock: Unstructured information processing for robot perception. elib (German Aerospace Center). 1549–1556. 45 indexed citations

8.

Nyga, Daniel, et al.. (2015). Towards robots conducting chemical experiments. 5202–5208. 16 indexed citations

9.

Nyga, Daniel, Ferenc Bálint-Benczédi, & Michael Beetz. (2014). PR2 looking at things — Ensemble learning for unstructured information processing with Markov logic networks. 3916–3923. 19 indexed citations

10.

Nyga, Daniel, et al.. (2014). Controlled Natural Languages for language generation in artificial cognition. 42. 6667–6672. 6 indexed citations

11.

Nyga, Daniel & Michael Beetz. (2012). Everything robots always wanted to know about housework (but were afraid to ask). 243–250. 32 indexed citations

12.

Nyga, Daniel, Moritz Tenorth, & Michael Beetz. (2011). How-models of human reaching movements in the context of everyday manipulation activities. 5. 6221–6226. 10 indexed citations

13.

Tenorth, Moritz, Daniel Nyga, & Michael Beetz. (2010). Understanding and executing instructions for everyday manipulation tasks from the World Wide Web. 1486–1491. 89 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact